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The key theorem of statistical learning theory with rough samples

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A key theorem of statistical learning theory with rough samples is proposed. The theorem provides a theoretical basis for the applied research of supporting vector machine etc. and therefore plays an important role in statistical learning theory. In view of the uncertainty of the real world, this paper combines the trust theory and statistical learning theory to generalize the key theorem of learning theory. Random samples are replaced with rough samples and rough empirical risk minimization principle is proposed. The theorem is proven in detail.

Original languageEnglish
Title of host publication2009 WRI World Congress on Software Engineering, WCSE 2009
Pages543-547
Number of pages5
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 WRI World Congress on Software Engineering, WCSE 2009 - Xiamen, China
Duration: 19 May 200921 May 2009

Publication series

Name2009 WRI World Congress on Software Engineering, WCSE 2009
Volume4

Conference

Conference2009 WRI World Congress on Software Engineering, WCSE 2009
Country/TerritoryChina
CityXiamen
Period19/05/0921/05/09

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